According to International Federation of Robotics, the total number of professional service robots sold in 2015 rose considerably by 25% to 41,060 units up from 32,939 in 2014. The sales value increased by 14% to US$ 4.6 billion. Since 1998, a total of about 220,000 service robots for professional use have been counted in these statistics. In 2015, about 5.4 million service robots for personal and domestic use were sold, 16% more than in 2014. The value of sales increased by 4% to US$2.2 billion.

After extensive modeling and the running of more than 100,000 simulations, an Artificial Intelligence (AI) system was given the task of predicting the 2018 FIFA champions. The AI predicted that Spain would be the champion (28.9% probability), followed by Germany (26.3%), and Brazil (21.9%). If we're going to get the most out of AI technology, we need to find ways to optimize both human and machine actions for best results. Research and consultancy firm Deloitte recommended viewing AI not as "thinking machines," but as cognitive prostheses that can help humans think better. One way to do this is by establishing accuracy checkpoints on AI outcomes.

With AI, it's time to scale up or give up,

This post by Dragana Pavlovic originally appeared on another Xerox blog, and it explains how artificial intelligence helps print workflow be more productive. If you take an interest in annual industry predictions, you'll have noticed artificial intelligence (AI) tops nearly every reputable 2018 list. Amidst the sensationalist claims of robots stealing human jobs and societal concerns about AI spinning out of control, PricewaterhouseCoopers (PwC) was on hand to ground the AI conversation firmly in the present. In its 2018 AI Predictions, PwC stated that 2018 is the year that "AI will come down to earth – and get to work." PwC predicts that in 2018 AI will finally start doing things, yet not necessarily in ways that set the world alight per certain overzealous media headlines.

Artificial intelligence in 2019 won't reach the level of the replicants of "Blade Runner" -- the 1982 movie that was set in this year -- but experts expect smart technology to become more common and more disruptive. Twenty percent of business executives told PwC consultants that their companies will begin to use AI in their businesses in 2019. Automation has already put plenty of people out of their jobs in recent years, but, according to PwC, 38 percent of business executives say AI will create more jobs, while only 19 percent say it will cause cuts. Sales of smart speakers like Amazon Echo and Google Home are expected to boom massively this year, with Deloitte consultants projecting the industry to surpass 250 million units sold by the end of 2019. But some expect the kickback to be strong, as users increasingly sour on big data collection and may push back on AI viewed as too overbearing and non-transparent.

Edward Tse is founder and CEO of Gao Feng Advisory Company, a strategy consultancy with roots in China assisting clients on global business and management issues. He previously headed Greater China operations for two major international management consulting firms for over 20 years, and is the author of The China Strategy and China's Disruptors.

We live in an age of disruption. Today, nearly every aspect of our professional and personal lives is coloured by unprecedented technological change to which organisations and their leaders need to respond--in fact, it will be key to their ability to successfully compete and thrive. By using technology, companies are weaving themselves into the very fabric of how people live, according to the global Accenture Technology Vision 2018 Survey. Thanks to emerging technologies, 'Intelligent Enterprises' are completely changing the way they do business. Through the use of these tools, organisations are not only meeting their business goals, but also benefiting citizens, communities and society.

Pilot projects of artificial intelligence (AI) technologies proliferated in 2018, as many enterprises tested machine learning (ML) algorithms and an array of automation tools to cement relationships with customers, improve network operations or augment their cybersecurity postures. Encouraged by early results, CIOs are preparing for the next challenge: scaling AI throughout the enterprise. Twenty percent of 1,000 U.S. business executives said their companies plan to implement AI across their enterprise in 2019, according to new research from PricewaterhouseCoopers (PwC). Get the latest insights with our CIO Daily newsletter. Companies are investing more in these emerging technologies, as IDC projects spending on cognitive and AI systems will reach $77.6 billion in 2022 -- more than three times the $24 billion forecast for 2018.

Everybody makes a list of 2019 predictions, but the folks at Deloitte have numbers behind theirs. As one of the world's biggest accounting and financial services firms, Deloitte is able to confidently predict that, for example, the smart speaker market will generate $7 billion in revenues in 2019. Below is Deloitte's 18th annual list of predictions for your enjoyment. "2019 will see massive improvements in a wide range of technologies, pushing once-novel innovations into the mainstreams of our lives and work," said Sandra Shirai, Deloitte's U.S. technology, media, and telecommunications leader, in a statement. "Emerging technologies are blurring traditional industry lines, impacting people and organizations; as a society, we'll be smarter, more productive, and more deeply engaged with the world around us." Deloitte said in its forecast that it expects 164 million smart speakers to sell in 2019 at an average price of $43.

It's been a while since businesses have been debating over investment into data and analytics. Some people have already done it and it is working out. We are over and above the apprehensions of whether Data investments work or not, now, the questions is how soon you can make it work. It has to be strategy first and a top down push on getting the data investments to execution and results. It is a herculean task but by now there are already best practices and open source tools to help adopt the data solutions.